STRING v9.1: protein-protein interaction networks, with increased coverage and integration

Identification and Pharmacological Targeting of Treatment-Resistant, Stem-like Breast Cancer Cells for Combination Therapy

Tumors frequently harbor isogenic yet epigenetically distinct subpopulations of multi-potent cells with high tumor-initiating potential-often called Cancer Stem-Like Cells (CSLCs). These can display preferential resistance to standard-of-care chemotherapy. Single-cell analyses can help elucidate Master Regulator (MR) proteins responsible for governing the transcriptional state of these cells, thus revealing complementary dependencies that may be leveraged via combination therapy. Interrogation of single-cell RNA sequencing profiles from seven metastatic breast cancer patients, using perturbational profiles of clinically relevant drugs, identified drugs predicted to invert the activity of MR proteins governing the transcriptional state of chemoresistant CSLCs, which were then validated by CROP-seq assays. The top drug, the anthelmintic albendazole, depleted this subpopulation in vivo without noticeable cytotoxicity. Moreover, sequential cycles of albendazole and paclitaxel-a commonly used chemotherapeutic -displayed significant synergy in a patient-derived xenograft (PDX) from a TNBC patient, suggesting that network-based approaches can help develop mechanism-based combinatorial therapies targeting complementary subpopulations.

White Isthmus Transcriptome Analysis Reveals the Mechanism of Translucent Eggshell Formation

The presence of translucent eggshells is a type of egg quality issue that impacts egg sales. While many researchers have studied them, the exact mechanisms behind their formation remain unclear. In this study, we conducted a transcriptomic differential expression analysis of the isthmus region of the oviduct in both normal egg- and translucent egg-laying hens. The analysis revealed that differentially expressed gene pathways were predominantly concentrated in the synthesis, modification, and transport of eggshell membrane proteins, particularly collagen proteins, which provide structural support. These findings suggest that variations in the physical structure of the eggshell membrane, resulting from changes in its chemical composition, are the fundamental cause of translucent eggshell formation. This research provides a theoretical reference for reducing the occurrence of translucent eggs.

A Carbon 21 Steroidal Glycoside with Pregnane Skeleton from Cynanchum atratum Bunge Promotes Megakaryocytic and Erythroid Differentiation in Erythroleukemia HEL Cells through Regulating Platelet-Derived Growth Factor Receptor Beta and JAK2/STAT3 Pathway

Erythroleukemia is a rare form of acute myeloid leukemia (AML). Its molecular pathogenesis remains vague, and this disease has no specific therapeutic treatments. Previously, our group isolated a series of Carbon 21 (C-21) steroidal glycosides with pregnane skeleton from the root of Cynanchum atratum Bunge. Among them, we found that a compound, named BW18, can induce S-phase cell cycle arrest and apoptosis via the mitogen-activated protein kinase (MAPK) pathway in human chronic myeloid leukemia K562 cells. However, its anti-tumor activity against erythroleukemia remains largely unknown. In this study, we aimed to investigate the anti-erythroleukemia activity of BW18 and the underlying molecular mechanisms. Our results demonstrated that BW18 exhibited a good anti-erythroleukemia activity in the human erythroleukemia cell line HEL and an in vivo xenograft mouse model. In addition, BW18 induced cell cycle arrest at the G2/M phase and promoted megakaryocytic and erythroid differentiation in HEL cells. Furthermore, RNA sequencing (RNA-seq) and rescue assay demonstrated that overexpression of platelet-derived growth factor receptor beta (PDGFRB) reversed BW18-induced megakaryocytic differentiation in HEL cells, but not erythroid differentiation. In addition, the network pharmacology analysis, the molecular docking and cellular thermal shift assay (CETSA) revealed that BW18 could inactivate Janus tyrosine kinase 2 (JAK2)/signal transducer and activator of transcription 3 (STAT3) pathway, which might mediate BW18-induced erythroid differentiation. Taken together, our findings elucidated a novel role of PDGFRB in regulating erythroleukemia differentiation and highlighted BW18 as an attractive lead compound for erythroleukemia treatment.

In Silico Analysis of Protein-Protein Interactions of Putative Endoplasmic Reticulum Metallopeptidase 1 in Schizosaccharomyces pombe

Ermp1 is a putative metalloprotease from Schizosaccharomyces pombe and a member of the Fxna peptidases. Although their function is unknown, orthologous proteins from rats and humans have been associated with the maturation of ovarian follicles and increased ER stress. This study focuses on proposing the first prediction of PPI by comparison of the interologues between humans and yeasts, as well as the molecular docking and dynamics of the M28 domain of Ermp1 with possible target proteins. As results, 45 proteins are proposed that could interact with the metalloprotease. Most of these proteins are related to the transport of Ca2+ and the metabolism of amino acids and proteins. Docking and molecular dynamics suggest that the M28 domain of Ermp1 could hydrolyze leucine and methionine residues of Amk2, Ypt5 and Pex12. These results could support future experimental investigations of other Fxna peptidases, such as human ERMP1.

Molecular evolution of Phytocyanin gene and analysis of expression at different coloring periods in apple (Malus domestica)

BACKGROUND

PC (phytocyanin) is a class of copper-containing electron transfer proteins closely related to plant photosynthesis, abiotic stress responses growth and development in plants, and regulation of the expression of some flavonoids and phenylpropanoids, etc., however, compared with other plants, the PC gene family has not been systematically characterized in apple.

RESULTS

A total of 59 MdPC gene members unevenly distributed across 12 chromosomes were identified at the genome-wide level. The proteins of the MdPC family were classified into four subfamilies based on differences in copper binding sites and glycosylation sites: Apple Early nodulin-like proteins (MdENODLs), Apple Uclacyanin-like proteins (MdUCLs), Apple Stellacyanin-like proteins (MdSCLs), and Apple Plantacyanin-like proteins (MdPLCLs). Some MdPC members with similar gene structures and conserved motifs belong to the same group or subfamily. The internal collinearity analysis revealed 14 collinearity gene pairs among members of the apple MdPC gene. Interspecific collinearity analysis showed that apple had 31 and 35 homologous gene pairs with strawberry and grape, respectively. Selection pressure analysis indicated that the MdPC gene was under purifying selection. Prediction of protein interactions showed that MdPC family members interacted strongly with the Nad3 protein. GO annotation results indicated that the MdPC gene also regulated the biosynthesis of phenylpropanoids. Chip data analysis showed that (MdSCL3, MdSCL7 and MdENODL27) were highly expressed in mature fruits and peels. Many cis-regulatory elements related to light response, phytohormones, abiotic stresses and flavonoid biosynthetic genes regulation were identified 2000 bp upstream of the promoter of the MdPC gene, and qRT-PCR results showed that gene members in Group IV (MdSCL1/3, MdENODL27) were up-regulated at all five stages of apple coloring, but the highest expression was observed at the DAF13 (day after fruit bag removal) stage. The gene members in Group II (MdUCL9, MdPLCL3) showed down-regulated or lower expression in the first four stages of apple coloring but up-regulated and highest expression in the DAF 21 stage.

CONCLUSION

Herein, one objective of these findings is to provide valuable information for understanding the structure, molecular evolution, and expression pattern of the MdPC gene, another major objective in this study was designed to lay the groundwork for further research on the molecular mechanism of PC gene regulation of apple fruit coloration.

Identification of Susceptibility Genes Underlying Bovine Respiratory Disease in Xinjiang Brown Cattle Based on DNA Methylation

DNA methylation is a form of epigenetic regulation, having pivotal parts in controlling cellular expansion and expression levels within genes. Although blood DNA methylation has been studied in humans and other species, its prominence in cattle is largely unknown. This study aimed to methodically probe the genomic methylation map of Xinjiang brown (XJB) cattle suffering from bovine respiratory disease (BRD), consequently widening cattle blood methylome ranges. Genome-wide DNA methylation profiling of the XJB blood was investigated through whole-genome bisulfite sequencing (WGBS). Many differentially methylated regions (DMRs) obtained by comparing the cases and controls groups were found within the CG, CHG, and CHH (where H is A, T, or C) sequences (16,765, 7502, and 2656, respectively), encompassing 4334 differentially methylated genes (DMGs). Furthermore, GO/KEGG analyses showed that some DMGs were involved within immune response pathways. Combining WGBS-Seq data and existing RNA-Seq data, we identified 71 significantly differentially methylated (DMGs) and expressed (DEGs) genes (p < 0.05). Next, complementary analyses identified nine DMGs (LTA, STAT3, IKBKG, IRAK1, NOD2, TLR2, TNFRSF1A, and IKBKB) that might be involved in the immune response of XJB cattle infected with respiratory diseases. Although further investigations are needed to confirm their exact implication in the involved immune processes, these genes could potentially be used for a marker-assisted selection of animals resistant to BRD. This study also provides new knowledge regarding epigenetic control for the bovine respiratory immune process.

Identification of MAD2L1 and BUB1B as Potential Biomarkers Associated with Progression and Prognosis of Ovarian Cancer

Ovarian cancer develops insidiously and is frequently diagnosed at advanced stages. Screening for ovarian cancer is an effective strategy for reducing mortality. This study aimed to investigate the molecular mechanisms underlying the development of ovarian cancer and identify novel tumor biomarkers for the diagnosis and prognosis of ovarian cancer. Three databases containing gene expression profiles specific to serous ovarian cancer (GSE18520, GSE12470, and GSE26712) were acquired. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes were analyzed for the differentially expressed gene (DEGs). The protein-protein interaction (PPI) network was constructed using the STRING database. The pivotal genes in the PPI network were screened using the Cytoscape software. Survival curve analysis was performed using a Kaplan-Meier Plotter. The cancer genome atlas and Gene Expression Omnibus databases were used to find the relationship between Hub gene and serous ovarian cancer. PCR and immunohistochemistry were used to detect the expression of Hub gene in serous ovarian cancer tissues and cells. Downstream pathways of the candidate tumor marker genes were predicted using Gene Set Enrichment Analysis. In this study, 252 DEGs were screened for pathway enrichment. 20 Hub genes were identified. Survival analysis suggested that Aurka, Bub1b, Cenpf, Cks1b, Kif20a, Mad2l1, Racgap1, and Ube2c were associated with the survival of patients with serous ovarian cancer. MAD2L1 and BUB1B levels were significantly different in serous ovarian cancer at different stages. Finally, Mad2l1 was found to play a role in the cell cycle, oocyte meiosis, and ubiquitin-mediated proteolysis. Meanwhile, Bub1b may play a role in the cell cycle, ubiquitin-mediated proteolysis, and spliceosome processes. Mad2l1 and Bub1b could be used as markers to predict ovarian carcinogenesis and prognosis, providing candidate targets for the diagnosis and treatment of serous ovarian cancer.

Identification of potential targetable genes in papillary, follicular, and anaplastic thyroid carcinoma using bioinformatics analysis

PURPOSE

To perform an extensive exploratory analysis to build a deeper insight into clinically relevant molecular biomarkers in Papillary, Follicular, and Anaplastic thyroid carcinomas (PTC, FTC, ATC).

METHODS

Thirteen Thyroid Cancer (THCA) datasets incorporating PTC, FTC, and ATC were derived from the Gene Expression Omnibus. Genes differentially expressed (DEGs) between THCA and normal were identified and subjected to GO and KEGG analyses. Multiple topological properties were harnessed and protein-protein interaction (PPI) networks were constructed to identify the hub genes followed by survival analysis and validation.

RESULTS

There were 70, 87, and 377 DEGs, and 23, 27, and 53 hub genes for PTC, FTC, and ATC samples, respectively. Survival analysis detected 39 overall and 49 relapse-free survival-relevant hub genes. Six hub genes, BCL2, FN1, ITPR1, LYVE1, NTRK2, TBC1D4, were found common to more than one THCA type. The most significant hub genes found in the study were: BCL2, CD44, DCN, FN1, IRS1, ITPR1, MFAP4, MKI67, NTRK2, PCLO, TGFA. The most enriched and significant GO terms were Melanocyte differentiation for PTC, Extracellular region for FTC, and Extracellular exosome for ATC. Prostate cancer for PTC was the most significantly enriched KEGG pathway. The results were validated using TCGA data.

CONCLUSIONS

The findings unravel potential biomarkers and therapeutic targets of thyroid carcinomas.

Metabolomics and proteomics insights into subacute ruminal acidosis etiology and inhibition of proliferation of yak rumen epithelial cells in vitro

BACKGROUND

Untargeted metabolomics and proteomics were employed to investigate the intracellular response of yak rumen epithelial cells (YRECs) to conditions mimicking subacute rumen acidosis (SARA) etiology, including exposure to short-chain fatty acids (SCFA), low pH5.5 (Acid), and lipopolysaccharide (LPS) exposure for 24 h.

RESULTS

These treatments significantly altered the cellular morphology of YRECs. Metabolomic analysis identified significant perturbations with SCFA, Acid and LPS treatment affecting 259, 245 and 196 metabolites (VIP > 1, P < 0.05, and fold change (FC) ≥ 1.5 or FC ≤ 0.667). Proteomic analysis revealed that treatment with SCFA, Acid, and LPS resulted in differential expression of 1251, 1396, and 242 proteins, respectively (FC ≥ 1.2 or ≤ 0.83, P < 0.05, FDR < 1%). Treatment with SCFA induced elevated levels of metabolites involved in purine metabolism, glutathione metabolism, and arginine biosynthesis, and dysregulated proteins associated with actin cytoskeleton organization and ribosome pathways. Furthermore, SCFA reduced the number, morphology, and functionality of mitochondria, leading to oxidative damage and inhibition of cell survival. Gene expression analysis revealed a decrease the genes expression of the cytoskeleton and cell cycle, while the genes expression associated with inflammation and autophagy increased (P < 0.05). Acid exposure altered metabolites related to purine metabolism, and affected proteins associated with complement and coagulation cascades and RNA degradation. Acid also leads to mitochondrial dysfunction, alterations in mitochondrial integrity, and reduced ATP generation. It also causes actin filaments to change from filamentous to punctate, affecting cellular cytoskeletal function, and increases inflammation-related molecules, indicating the promotion of inflammatory responses and cellular damage (P < 0.05). LPS treatment induced differential expression of proteins involved in the TNF signaling pathway and cytokine-cytokine receptor interaction, accompanied by alterations in metabolites associated with arachidonic acid metabolism and MAPK signaling (P < 0.05). The inflammatory response and activation of signaling pathways induced by LPS treatment were also confirmed through protein interaction network analysis. The integrated analysis reveals co-enrichment of proteins and metabolites in cellular signaling and metabolic pathways.

CONCLUSIONS

In summary, this study contributes to a comprehensive understanding of the detrimental effects of SARA-associated factors on YRECs, elucidating their molecular mechanisms and providing potential therapeutic targets for mitigating SARA.

Tumors Established in a Defective Immune Environment Reprogram the Oncogenic Signaling Pathways to Escalate Tumor Antigenicity

Tumors developed in immunocompromised hosts are more immunogenic. However, few studies have addressed the potential mechanisms underlying the high immunogenicity of tumors found in a suppressed immune system. Therefore, we aimed to elucidate the impacts of the immune system on tumor behaviors and immunogenicity sculpting. A murine colorectal adenocarcinoma cell line, CT26wt, was administrated into immunocompetent (BALB/c) and immunocompromised (NOD.SCID) mice, respectively. On day 11, the CT26 cells slowly progressed in the NOD.SCID mice compared to the BALB/c mice. We then performed liquid chromatography-tandem mass spectrometry (LC-MS/MS) and analyzed the differentially expressed proteins (DEPs). The DEPs participated in numerous oncogenic pathways, PI3K/AKT/mTOR cell signaling, and the silencing of several tumor suppressors, such as PTEN and RBL1, during tumorigenesis. On day 34, the CT26/SCID tumors inversely became malignant counterparts; then the CT26/SCID tumors were harvested and re-inoculated into immunocompetent mice (CT26/SCID-Re tumors) to determine the immunogenicity. The CT26/SCID-Re tumor growth rate significantly decreased. Furthermore, increased infiltrations of dendritic cells and tumor-infiltrating T lymphocytes were found in the CT26/SCID-Re tumors. These findings suggest that immunogenic tumors might express multiple tumor rejection antigens, unlike wild-type tumors, and attract more immune cells, therefore decreasing the growth rate. Collectively, our study first revealed that in immunodeficient hosts, tumor suppressors were silenced and oncogenic signaling pathways were changed during the initial phase of tumor development. With tumor progression, the tumor antigens were overexpressed, exhibiting elevated immunogenicity. This study offers a hint on the mechanisms of tumorigenesis and provides a niche for investigating the interaction between host immunity and cancer development.

Leaf gene expression trajectories during the growing season are consistent between sites and years in American beech

Transcriptomics provides a versatile tool for ecological monitoring. Here, through genome-guided profiling of transcripts mapping to 33 042 gene models, expression differences can be discerned among multi-year and seasonal leaf samples collected from American beech trees at two latitudinally separated sites. Despite a bottleneck due to post-Columbian deforestation, the single nucleotide polymorphism-based population genetic background analysis has yielded sufficient variation to account for differences between populations and among individuals. Our expression analyses during spring-summer and summer-autumn transitions for two consecutive years involved 4197 differentially expressed protein coding genes. Using Populus orthologues we reconstructed a protein-protein interactome representing leaf physiological states of trees during the seasonal transitions. Gene set enrichment analysis revealed gene ontology terms that highlight molecular functions and biological processes possibly influenced by abiotic forcings such as recovery from drought and response to excess precipitation. Further, based on 324 co-regulated transcripts, we focused on a subset of GO terms that could be putatively attributed to late spring phenological shifts. Our conservative results indicate that extended transcriptome-based monitoring of forests can capture diverse ranges of responses including air quality, chronic disease, as well as herbivore outbreaks that require activation and/or downregulation of genes collectively tuning reaction norms maintaining the survival of long living trees such as the American beech.

Comprehensive CCM3 Mutational Analysis in Two Patients with Syndromic Cerebral Cavernous Malformation

Cerebral cavernous malformation (CCM) is a vascular disease that affects the central nervous system, which familial form is due to autosomal dominant mutations in the genes KRIT1(CCM1), MGC4607(CCM2), and PDCD10(CCM3). Patients affected by the PDCD10 mutations usually have the onset of symptoms at an early age and a more aggressive phenotype. The aim of this study is to investigate the molecular mechanism involved with CCM3 disease pathogenesis. Herein, we report two typical cases of CCM3 phenotype and compare the clinical and neuroradiological findings with five patients with a familial form of KRIT1 or CCM2 mutations and six patients with a sporadic form. In addition, we evaluated the PDCD10 gene expression by qPCR and developed a bioinformatic pipeline to understand the structural changes of mutations. The two CCM3 patients had an early onset of symptoms and a high lesion burden. Furthermore, the sequencing showed that Patient 1 had a frameshift mutation in c.222delT; p.(Asn75Thrfs*14) that leads to lacking the last 124 C-terminal amino acids on its primary structure and Patient 2 had a variant on the splicing site region c.475-2A > G. The mRNA expression was fourfold lower in both patients with PDCD10 mutation. Using in silico analysis, we identify that the frameshift mutation transcript lacks the C-terminal FAT-homology domain compared to the wild-type PDCD10 and preserves the N-terminal dimerization domain. The two patients studied here allow estimating the potential impact of mutations in clinical interpretation as well as support to better understand the mechanism and pathogenesis of CCM3.

Investigation of two-pore K+ (TPK) channels in Triticum aestivum L. suggests their role in stress response

Two-pore K+ (TPK) channels are voltage-independent and involved in stress response in plants. Herein, we identified 12 TaTPK genes located on nine chromosomes in the Triticum aestivum genome. The majority of TaTPK genes comprised two exons. Each TaTPK channel comprised four transmembrane (TM) helices, N- and C-terminal ion-channel domains, two EF-hand domains and one 14-3-3 binding site. Additionally, highly conserved 'GYGD' motif responsible for K+ ion specificity, was found in between the TMs in both the ion-channel domains. Nine TaTPK channels were predicted to be localised at the plasma membrane, while three were vacuolar. The protein-protein and protein-chemical interactions indicated the coordinated functioning of the TaTPK channels with the other K+ transporters and their possible interaction with the Ca2+-signaling pathway. Expression studies suggested their importance in both vegetative and reproductive tissues development. Significantly modulated expression of various TaTPK genes during heat, drought, combined heat and drought and salt stresses, and after fungal infestation, depicted their function in stress responses. The miRNAs and transcription factors interaction analyses suggested their role in the hormone, light, growth and development-related, and stress-responsive signaling cascades. The current study suggested vital functions of various TaTPK genes, especially in stress response, and would provide an opportunity for their detailed characterization in future studies.

Phosphoregulation in the N-terminus of NRT2.1 affects nitrate uptake by controlling the interaction of NRT2.1 with NAR2.1 and kinase HPCAL1 in Arabidopsis

NRT2.1, the major high affinity nitrate transporter in roots, can be phosphorylated at five different sites within the N- and the C-terminus. Here, we characterized the functional relationship of two N-terminal phosphorylation sites, S21 and S28, in Arabidopsis. Based on a site-specific correlation network, we identified a receptor kinase (HPCAL1, AT5G49770), phosphorylating NRT2.1 at S21 and resulting in active nitrate uptake. HPCAL1 itself was regulated by phosphorylation at S839 and S870 within its kinase domain. In the active state, when S839 was dephosphorylated and S870 was phosphorylated, HPCAL1 was found to interact with the N-terminus of NRT2.1, mainly when S28 was dephosphorylated. Phosphorylation of NRT2.1 at S21 resulted in a reduced interaction of NRT2.1 with its activator NAR2.1, but nitrate transport activity remained. By contrast, phosphorylated NRT2.1 at S28 enhanced the interaction with NAR2.1, but reduced the interaction with HPCAL1. Here we identified HPCAL1 as the kinase affecting this phospho-switch through phosphorylation of NRT2.1 at S21.

Mass spectrometry-based proteomics profiling of dogs with and without oral diseases: a systematic review

BACKGROUND

Understanding the distinct proteomics profiles in dogs' oral biofluids enhances diagnostic and therapeutic insights for canine oral diseases, fostering cross-species translational research in dentistry and medicine. This study aimed to conduct a systematic review to investigate the similarities and differences between the oral biofluids' proteomics profile of dogs with and without oral diseases.

METHODS

PubMed, Web of Science, and Scopus were searched with no restrictions on publication language or year to address the following focused question: "What is the proteome signature of healthy versus diseased (oral) dogs' biofluids?" Gene Ontology enrichment and the Kyoto Encyclopedia of Genes and Genomes pathway analyses of the most abundant proteins were performed. Moreover, protein-protein interaction analysis was conducted. The risk of bias (RoB) among the included studies was assessed using the Joanna Briggs Institute (JBI) Critical Appraisal Checklist for Studies Reporting Prevalence Data.

RESULTS

In healthy dogs, the proteomic analysis identified 5,451 proteins, with 137 being the most abundant, predominantly associated with 'innate immune response'. Dogs with oral diseases displayed 6,470 proteins, with distinct associations: 'defense response to bacterium' (periodontal diseases), 'negative regulation of transcription' (dental calculus), and 'positive regulation of transcription' (oral tumors). Clustering revealed significant protein clusters in each case, emphasizing the diverse molecular profiles in health and oral diseases. Only six studies were provided to the JBI tool, as they encompassed case-control evaluations that compared healthy dogs to dogs with oral disease(s). All included studies were found to have low RoB (high quality).

CONCLUSION

Significant differences in the proteomics profiles of oral biofluids between dogs with and without oral diseases were found. The synergy of animal proteomics and bioinformatics offers a promising avenue for cross-species research, despite persistent challenges in result validation.

Analysis and experimental validation of IL-17 pathway and key genes as central roles associated with inflammation in hepatic ischemia-reperfusion injury

Hepatic ischemia-reperfusion injury (HIRI) elicits an immune-inflammatory response that may result in hepatocyte necrosis and apoptosis, ultimately culminating in postoperative hepatic dysfunction and hepatic failure. The precise mechanisms governing the pathophysiology of HIRI remain incompletely understood, necessitating further investigation into key molecules and pathways implicated in disease progression to guide drug discovery and potential therapeutic interventions. Gene microarray data was downloaded from the GEO expression profile database. Integrated bioinformatic analyses were performed to identify HIRI signature genes, which were subsequently validated for expression levels and diagnostic efficacy. Finally, the gene expression was verified in an experimental HIRI model and the effect of anti-IL17A antibody intervention in three time points (including pre-ischemic, post-ischemic, and at 1 h of reperfusion) on HIRI and the expression of these genes was investigated. Bioinformatic analyses of the screened characterized genes revealed that inflammation, immune response, and cell death modulation were significantly associated with HIRI pathophysiology. CCL2, BTG2, GADD45A, FOS, CXCL10, TNFRSF12A, and IL-17 pathway were identified as key components involved in the HIRI. Serum and liver IL-17A expression were significantly upregulated during the initial phase of HIRI. Pretreatment with anti-IL-17A antibody effectively alleviated the damage of liver tissue, suppressed inflammatory factors, and serum transaminase levels, and downregulated the mRNA expression of CCL2, GADD45A, FOS, CXCL10, and TNFRSF12A. Injection of anti-IL17A antibody after ischemia and at 1 h of reperfusion failed to demonstrate anti-inflammatory and attenuating HIRI benefits relative to earlier intervention. Our study reveals that the IL-17 pathway and related genes may be involved in the proinflammatory mechanism of HIRI, which may provide a new perspective and theoretical basis for the prevention and treatment of HIRI.

Identification of a novel inflammatory-related gene signature to evaluate the prognosis of gastric cancer patients

BACKGROUND

Gastric cancer (GC) is a highly aggressive malignancy with a heterogeneous nature, which makes prognosis prediction and treatment determination difficult. Inflammation is now recognized as one of the hallmarks of cancer and plays an important role in the aetiology and continued growth of tumours. Inflammation also affects the prognosis of GC patients. Recent reports suggest that a number of inflammatory-related biomarkers are useful for predicting tumour prognosis. However, the importance of inflammatory-related biomarkers in predicting the prognosis of GC patients is still unclear.

AIM

To investigate inflammatory-related biomarkers in predicting the prognosis of GC patients.

METHODS

In this study, the mRNA expression profiles and corresponding clinical information of GC patients were obtained from the Gene Expression Omnibus (GEO) database (GSE66229). An inflammatory-related gene prognostic signature model was constructed using the least absolute shrinkage and selection operator Cox regression model based on the GEO database. GC patients from the GSE26253 cohort were used for validation. Univariate and multivariate Cox analyses were used to determine the independent prognostic factors, and a prognostic nomogram was established. The calibration curve and the area under the curve based on receiver operating characteristic analysis were utilized to evaluate the predictive value of the nomogram. The decision curve analysis results were plotted to quantify and assess the clinical value of the nomogram. Gene set enrichment analysis was performed to explore the potential regulatory pathways involved. The relationship between tumour immune infiltration status and risk score was analysed via Tumour Immune Estimation Resource and CIBERSORT. Finally, we analysed the association between risk score and patient sensitivity to commonly used chemotherapy and targeted therapy agents.

RESULTS

A prognostic model consisting of three inflammatory-related genes (MRPS17, GUF1, and PDK4) was constructed. Independent prognostic analysis revealed that the risk score was a separate prognostic factor in GC patients. According to the risk score, GC patients were stratified into high- and low-risk groups, and patients in the high-risk group had significantly worse prognoses according to age, sex, TNM stage and Lauren type. Consensus clustering identified three subtypes of inflammation that could predict GC prognosis more accurately than traditional grading and staging. Finally, the study revealed that patients in the low-risk group were more sensitive to certain drugs than were those in the high-risk group, indicating a link between inflammation-related genes and drug sensitivity.

CONCLUSION

In conclusion, we established a novel three-gene prognostic signature that may be useful for predicting the prognosis and personalizing treatment decisions of GC patients.

Colonization of root endophytic fungus Serendipita indica improves drought tolerance of Pinus taeda seedlings by regulating metabolome and proteome

Pinus taeda is an important forest tree species for plantations because of its rapid growth and high yield of oleoresins. Although P. taeda plantations distribute in warm and wet southern China, drought, sometime serious and long time, often occurs in the region. To explore drought tolerance of P. taeda and usage of beneficial microorganisms, P. taeda seedlings were planted in pots and were inoculated with root endophytic fungus Serendipita indica and finally were treated with drought stress for 53 d. Metabolome and proteome of their needles were analyzed. The results showed that S. indica inoculation of P. taeda seedlings under drought stress caused great changes in levels of some metabolites in their needles, especially some flavonoids and organic acids. Among them, the levels of eriocitrin, trans-aconitic acid, vitamin C, uric acid, alpha-ketoglutaric acid, vitamin A, stachydrine, coumalic acid, itaconic acid, calceolarioside B, 2-oxoglutaric acid, and citric acid were upregulated more than three times in inoculated seedlings under drought stress, compared to those of non-inoculated seedlings under drought stress. KEGG analysis showed that some pathways were enriched in inoculated seedlings under drought stress, such as flavonoid biosynthesis, ascorbate and aldarate metabolism, C5-branched dibasic acid metabolism. Proteome analysis revealed some specific differential proteins. Two proteins, namely, H9X056 and H9VDW5, only appeared in the needles of inoculated seedlings under drought stress. The protein H9VNE7 was upregulated more than 11.0 times as that of non-inoculated seedlings under drought stress. In addition, S. indica inoculation increased enrichment of water deficient-inducible proteins (such as LP3-1, LP3-2, LP3-3, and dehydrins) and those involved in ribosomal structures (such as A0A385JF23). Meanwhile, under drought stress, the inoculation caused great changes in biosynthesis and metabolism pathways, mainly including phenylpropanoid biosynthesis, cutin, suberine and wax biosynthesis, and 2-oxocarboxylic acid metabolism. In addition, there were positive relationships between accumulation of some metabolites and enrichment of proteins in P. taeda under drought stress. Altogether, our results showed great changes in metabolome and proteome in inoculated seedlings under drought stress and provided a guideline to further study functions of metabolites and proteins, especially those related to drought stress.

RGS4 Actions in Mouse Prefrontal Cortex Modulate Behavioral and Transcriptomic Responses to Chronic Stress and Ketamine

The signal transduction protein, regulator of G protein signaling 4 (RGS4), plays a prominent role in physiologic and pharmacological responses by controlling multiple intracellular pathways. Our earlier work identified the dynamic but distinct roles of RGS4 in the efficacy of monoamine-targeting versus fast-acting antidepressants. Using a modified chronic variable stress (CVS) paradigm in mice, we demonstrate that stress-induced behavioral abnormalities are associated with the downregulation of RGS4 in the medial prefrontal cortex (mPFC). Knockout of RGS4 (RGS4KO) increases susceptibility to CVS, as mutant mice develop behavioral abnormalities as early as 2 weeks after CVS resting-state functional magnetic resonance imaging I (rs-fMRI) experiments indicate that stress susceptibility in RGS4KO mice is associated with changes in connectivity between the mediodorsal thalamus (MD-THL) and the mPFC. Notably, RGS4KO also paradoxically enhances the antidepressant efficacy of ketamine in the CVS paradigm. RNA-sequencing analysis of naive and CVS samples obtained from mPFC reveals that RGS4KO triggers unique gene expression signatures and affects several intracellular pathways associated with human major depressive disorder. Our analysis suggests that ketamine treatment in the RGS4KO group triggers changes in pathways implicated in synaptic activity and responses to stress, including pathways associated with axonal guidance and myelination. Overall, we show that reducing RGS4 activity triggers unique gene expression adaptations that contribute to chronic stress disorders and that RGS4 is a negative modulator of ketamine actions. SIGNIFICANCE STATEMENT: Chronic stress promotes robust maladaptation in the brain, but the exact intracellular pathways contributing to stress vulnerability and mood disorders have not been thoroughly investigated. In this study, the authors used murine models of chronic stress and multiple methodologies to demonstrate the critical role of the signal transduction modulator regulator of G protein signaling 4 in the medial prefrontal cortex in vulnerability to chronic stress and the efficacy of the fast-acting antidepressant ketamine.

In Silico Analysis of Glutamate Receptors in Capsicum chinense: Structure, Evolution, and Molecular Interactions

Plant glutamate receptors (GLRs) are integral membrane proteins that function as non-selective cation channels, involved in the regulation of developmental events crucial in plants. Knowledge of these proteins is restricted to a few species and their true agonists are still unknown in plants. Using tomato SlGLRs, a search was performed in the pepper database to identify GLR sequences in habanero pepper (Capsicum chinense Jacq.). Structural, phylogenetic, and orthology analysis of the CcGLRs, as well as molecular docking and protein interaction networks, were conducted. Seventeen CcGLRs were identified, which contained the characteristic domains of GLR. The variation of conserved residues in the M2 transmembrane domain between members suggests a difference in ion selectivity and/or conduction. Also, new conserved motifs in the ligand-binding regions are reported. Duplication events seem to drive the expansion of the species, and these were located in the evolution by using orthologs. Molecular docking analysis allowed us to identify differences in the agonist binding pocket between CcGLRs, which suggest the existence of different affinities for amino acids. The possible interaction of some CcGLRs with proteins leads to suggesting specific functions for them within the plant. These results offer important functional clues for CcGLR, probably extrapolated to other Solanaceae.

Crosstalk of cell death pathways unveils an autophagy-related gene AOC3 as a critical prognostic marker in colorectal cancer

The intricate crosstalk of various cell death forms was recently implicated in cancers, laying a foundation for exploring the association between cell death and cancers. Recent evidence has demonstrated that biological networks outperform snapshot gene expression profiles at discovering promising biomarkers or heterogenous molecular subtypes across different cancer types. In order to investigate the behavioral patterns of cell death-related interaction perturbation in colorectal cancer (CRC), this study constructed the interaction-perturbation network with 11 cell death pathways and delineated four cell death network (CDN) derived heterogeneous subtypes (CDN1-4) with distinct molecular characteristics and clinical outcomes. Specifically, we identified a subtype (CDN4) endowed with high autophagy activity and the worst prognosis. Furthermore, AOC3 was identified as a potential autophagy-related biomarker, which demonstrated exceptional predictive performance for CDN4 and significant prognostic value. Overall, this study sheds light on the complex interplay of various cell death forms and reveals an autophagy-related gene AOC3 as a critical prognostic marker in CRC.

Genomic and Expression Analysis of Cassava (Manihot esculenta Crantz) Chalcone Synthase Genes in Defense against Tetranychus cinnabarinus Infestation

Cassava is susceptible to mites, especially Tetranychus cinnabarinus. Secondary metabolism products such as flavonoids play an important role as antimicrobial metabolites protecting plants against biotic stressors including fungal, pathogen, bacterial, and pest defense. The chalcone synthase (CHS) is the initial step of the phenylpropanoid pathway for producing flavonoids and is the gatekeeper of the pathway. Until recently, the CHS genes family has not been systematically studied in cassava. Thirty-nine CHS genes were identified from the cassava genome database. Based on phylogenetic and sequence composition analysis, these CHSs were divided into 3 subfamilies. Within the same subfamily, the gene structure and motif compositions of these CHS genes were found to be quite conserved. Duplication events, particularly segmental duplication of the cassava CHS genes, were identified as one of the main driving force of its expansion. Various cis-elements contained in the promoter might regulate the gene expression patterns of MeCHS. Protein-protein interaction (PPI) network analysis showed that MeCHS1 and MeCHS10 protein are more closely related to other family members. The expression of MeCHS genes in young leaves was higher than that in other tissues, and their expression varies even within the same tissue. Coincidentally, these CHS genes of most LAP subclasses were highly expressed in young leaves. The verified MeCHS genes showed consistent with the real-time reverse transcription quantitative PCR (RT-qPCR) and proteomic expression in protected and affected leaves respectively, indicating that these MeCHS genes play crucial roles in the response to T. cinnabarinus. This study is the first to comprehensively expatiate the information on MeCHS family members. These data will further enhance our understanding both the molecular mechanisms and the effects of CHS genes. In addition, the results will help to further clarify the effects on T. cinnabarinus and provide a theoretical basis for the potential functions of the specific CHS gene in resistance to mites and other biotic stress.

Salivary protein homology between humans and dogs: Mass spectrometry-based proteomics analysis

OBJECTIVE

This benchmark study aimed to investigate sex-related differences based on the identification and characterization of the salivary proteome of healthy male and female dogs using mass spectrometry (MS) technique and a homology-driven approach to analyze salivary proteins in both human and dog species utilizing protein sequence alignment technique.

METHODS

Unstimulated whole saliva was collected from 10 healthy Beagles. After processing the samples and determining the total protein content, in-solution protein digestion was performed involving denaturation, reduction of disulfide bonds, alkylation, and removal of interfering compounds. Samples were analyzed using LC-ESI-MS/MS.

RESULTS

LC-ESI-MS/MS analysis identified 327 and 341 unique proteins in male and female dog saliva, respectively, of which 318 (97.25 %) in male dogs and 326 (95.60 %) in female dogs were characterized. Abundant shared proteins included albumin, BPI fold-containing family A member 2, and VWFD domain-containing protein. A notable uncharacterized protein, VWFD domain-containing protein, was among the most abundant in both sexes. Comparative analysis of 69 abundant shared proteins indicated an upregulation of CES5A, EFHD, GC, IGHM, LOC100653049, KRT10, LCP1, PGD, TPI1 in male dogs, while LOC100855593 was upregulated in female dogs. In total, 84 % (n = 229/274) and 86 % (n = 235/275) salivary proteins identified in male and female dogs, respectively, were homologous to human proteins, with an overall homology of 86 % (n = 364/423), including 15 with 100 % homology.

CONCLUSION

The study revealed clear differences in the salivary proteomics profile of healthy male and female dogs. However, most of the salivary proteins in both male and female dogs showed homology with human salivary proteins.

CLINICAL RELEVANCE

The identification of unique salivary proteome profiles in male and female dogs, coupled with substantial homology to human proteins, provides promising biomarkers for health assessment, highlighting its clinical significance for diagnostics and therapeutic exploration not only in veterinary and human dentistry, but across mammalian species.

A critical review on bioaerosols-dispersal of crop pathogenic microorganisms and their impact on crop yield

Bioaerosols are potential sources of pathogenic microorganisms that can cause devastating outbreaks of global crop diseases. Various microorganisms, insects and viroids are known to cause severe crop diseases impeding global agro-economy. Such losses threaten global food security, as it is estimated that almost 821 million people are underfed due to global crisis in food production. It is estimated that global population would reach 10 billion by 2050. Hence, it is imperative to substantially increase global food production to about 60% more than the existing levels. To meet the increasing demand, it is essential to control crop diseases and increase yield. Better understanding of the dispersive nature of bioaerosols, seasonal variations, regional diversity and load would enable in formulating improved strategies to control disease severity, onset and spread. Further, insights on regional and global bioaerosol composition and dissemination would help in predicting and preventing endemic and epidemic outbreaks of crop diseases. Advanced knowledge of the factors influencing disease onset and progress, mechanism of pathogen attachment and penetration, dispersal of pathogens, life cycle and the mode of infection, aid the development and implementation of species-specific and region-specific preventive strategies to control crop diseases. Intriguingly, development of R gene-mediated resistant varieties has shown promising results in controlling crop diseases. Forthcoming studies on the development of an appropriately stacked R gene with a wide range of resistance to crop diseases would enable proper management and yield. The article reviews various aspects of pathogenic bioaerosols, pathogen invasion and infestation, crop diseases and yield.

Uncovering co-regulatory modules and gene regulatory networks in the heart through machine learning-based analysis of large-scale epigenomic data

The availability of large-scale epigenomic data from various cell types and conditions has yielded valuable insights for evaluating and learning features predicting the co-binding of transcription factors (TF). However, prior attempts to develop models predicting motif co-occurrence lacked scalability for globally analyzing any motif combination or making cross-species predictions. Moreover, mapping co-regulatory modules (CRM) to gene regulatory networks (GRN) is crucial for understanding underlying function. Currently, no comprehensive pipeline exists for large-scale, rapid, and accurate CRM and GRN identification. In this study, we analyzed and evaluated different TF binding characteristics facilitating biologically significant co-binding to identify all potential clusters of co-binding TFs. We curated the UniBind database, containing ChIP-Seq data from over 1983 samples and 232 TFs, and implemented two machine learning models to predict CRMs and the potential regulatory networks they operate on. Two machine learning models, Convolution Neural Networks (CNN) and Random Forest Classifier(RFC), used to predict co-binding between TFs, were compared using precision-recall Receiver Operating Characteristic (ROC) curves. CNN outperformed RFC (AUC 0.94 vs. 0.88) and achieved higher F1 scores (0.938 vs. 0.872). The CRMs generated by the clustering algorithm were validated against ChipAtlas and MCOT, revealing additional motifs forming CRMs. We predicted 200k CRMs for 50k+ human genes, validated against recent CRM prediction methods with 100% overlap. Further, we narrowed our focus to study heart-related regulatory motifs, filtering the generated CRMs to report 1784 Cardiac CRMs containing at least four cardiac TFs. Identified cardiac CRMs revealed potential novel regulators like ARID3A and RXRB for SCAD, including known TFs like PPARG for F11R. Our findings highlight the importance of the NKX family of transcription factors in cardiac development and provide potential targets for further investigation in cardiac disease.

Viral integration promotes SV40T-induced immortalization by disturbing the expression of DNA/chromosome- and ECM-associated functional genes

Lentivirus containing simian virus 40 large T antigen (SV40T) is routinely used to induce cell immortalization. However, the roles of viral integration itself in this progress is still controversial. Here, we transformed primary mouse embryonic fibroblasts (MEFs) with SV40T lentivirus and studied the roles of viral integration in the immortalization using RNA sequencing (RNA-seq) and whole genome sequencing (WGS). During the immortalization, differentially expressed genes (DGEs) are enriched in viral infection and several diverse activities. However, DEGs between immortalized and aging cells are significantly enriched in DNA/chromosome- and extracellular matrix (ECM)-associated activities. Gene regulatory network (GRN) analysis shows that although p53 is a key regulatory factor, many other transcription factors also play critical roles in the process, like STAT1. Of these DEGs, 32 genes have viral integration in their coding and/or regulatory regions. Our findings suggest that viral integration may promote SV40T-mediated immortalization by disturbing the expression of DNA/chromosome- and ECM-associated genes.

Comprehensive analysis identifies crucial genes associated with immune cells mediating progression of carotid atherosclerotic plaque

BACKGROUNDS

Carotid atherosclerosis is prone to rupture and cause ischemic stroke in advanced stages of development. Our research aims to provide markers for the progression of atherosclerosis and potential targets for its treatment.

METHODS

We performed a thorough analysis using various techniques including DEGs, GO/KEGG, xCell, WGCNA, GSEA, and other methods. The gene expression omnibus datasets GSE28829 and GSE43292 were utilized for this comprehensive analysis. The validation datasets employed in this study consisted of GSE41571 and GSE120521 datasets. Finally, we validated PLEK by immunohistochemistry staining in clinical samples.

RESULTS

Using the WGCNA technique, we discovered 636 differentially expressed genes (DEGs) and obtained 12 co-expression modules. Additionally, we discovered two modules that were specifically associated with atherosclerotic plaque. A total of 330 genes that were both present in DEGs and WGCNA results were used to create a protein-protein network in Cytoscape. We used four different algorithms to get the top 10 genes and finally got 6 overlapped genes (TYROBP, ITGB2, ITGAM, PLEK, LCP2, CD86), which are identified by GSE41571 and GSE120521 datasets. Interestingly, the area under curves (AUC) of PLEK is 0.833. Besides, we found PLEK is strongly positively correlated with most lymphocytes and myeloid cells, especially monocytes and macrophages, and negatively correlated with most stromal cells (e.g, neurons, myocytes, and fibroblasts). The expression of PLEK were consistent with the immunohistochemistry results.

CONCLUSIONS

Six genes (TYROBP, ITGB2, ITGAM, PLEK, LCP2, CD86) were found to be connected with carotid atherosclerotic plaques and PLEK may be an important biomarker and a potential therapeutic target.

Targets and Effects of Common Biocompounds of Hibiscus sabdariffa (Delphinidin-3-Sambubiosid, Quercetin, and Hibiscus Acid) in Different Pathways of Human Cells According to a Bioinformatic Assay

The utilization of food as a therapeutic measure for various ailments has been a prevalent practice throughout history and across different cultures. This is exemplified in societies where substances like Hibiscus sabdariffa have been employed to manage health conditions like hypertension and elevated blood glucose levels. The inherent bioactive compounds found in this plant, namely, delphinidin-3-sambubioside (DS3), quercetin (QRC), and hibiscus acid (HA), have been linked to various health benefits. Despite receiving individual attention, the specific molecular targets for these compounds remain unclear. In this study, computational analysis was conducted using bioinformatics tools such as Swiss Target Prediction, ShinnyGo 0.77, KEGG, and Stringdb to identify the molecular targets, pathways, and hub genes. Supplementary results were obtained through a thorough literature search in PubMed. DS3 analysis revealed potential genetic alterations related to the metabolism of nitrogen and glucose, inflammation, angiogenesis, and cell proliferation, particularly impacting the PI3K-AKT signaling pathway. QRC analysis demonstrated interconnected targets spanning multiple pathways, with some overlap with DS3 analysis and a particular focus on pathways related to cancer. HA analysis revealed distinct targets, especially those associated with pathways related to the nervous system. These findings emphasize the necessity for focused research on the molecular effects of DS3, QRC, and HA, thereby providing valuable insights into potential therapeutic pathways.

Proteomics and Its Current Application in Biomedical Area: Concise Review

Biomedical researchers tirelessly seek cutting-edge technologies to advance disease diagnosis, drug discovery, and therapeutic interventions, all aimed at enhancing human and animal well-being. Within this realm, proteomics stands out as a pivotal technology, focusing on extensive studies of protein composition, structure, function, and interactions. Proteomics, with its subdivisions of expression, structural, and functional proteomics, plays a crucial role in unraveling the complexities of biological systems. Various sophisticated techniques are employed in proteomics, including polyacrylamide gel electrophoresis, mass spectrometry analysis, NMR spectroscopy, protein microarray, X-ray crystallography, and Edman sequencing. These methods collectively contribute to the comprehensive understanding of proteins and their roles in health and disease. In the biomedical field, proteomics finds widespread application in cancer research and diagnosis, stem cell studies, and the diagnosis and research of both infectious and noninfectious diseases. In addition, it plays a pivotal role in drug discovery and the emerging frontier of personalized medicine. The versatility of proteomics allows researchers to delve into the intricacies of molecular mechanisms, paving the way for innovative therapeutic approaches. As infectious and noninfectious diseases continue to emerge and the field of biomedical research expands, the significance of proteomics becomes increasingly evident. Keeping abreast of the latest developments in proteomics applications becomes paramount for the development of therapeutics, translational research, and study of diverse diseases. This review aims to provide a comprehensive overview of proteomics, offering a concise outline of its current applications in the biomedical domain. By doing so, it seeks to contribute to the understanding and advancement of proteomics, emphasizing its pivotal role in shaping the future of biomedical research and therapeutic interventions.

Volatile Compounds Emitted by Plant Growth-Promoting Fungus Tolypocladium inflatum GT22 Alleviate Copper and Pathogen Stress

Previous studies on the intricate interactions between plants and microorganisms have revealed that fungal volatile compounds (VCs) can affect plant growth and development. However, the precise mechanisms underlying these actions remain to be delineated. In this study, we discovered that VCs from the soilborne fungus Tolypocladium inflatum GT22 enhance the growth of Arabidopsis. Remarkably, priming Arabidopsis with GT22 VCs caused the plant to display an enhanced immune response and mitigated the detrimental effects of both pathogenic infections and copper stress. Transcriptomic analyses of Arabidopsis seedlings treated with GT22 VCs for 3, 24 and 48 h revealed that 90, 83 and 137 genes were differentially expressed, respectively. The responsive genes are known to be involved in growth, hormone regulation, defense mechanisms and signaling pathways. Furthermore, we observed the induction of genes related to innate immunity, hypoxia, salicylic acid biosynthesis and camalexin biosynthesis by GT22 VCs. Among the VCs emitted by GT22, exposure of Arabidopsis seedlings to limonene promoted plant growth and attenuated copper stress. Thus, limonene appears to be a key mediator of the interaction between GT22 and plants. Overall, our findings provide evidence that fungal VCs can promote plant growth and enhance both biotic and abiotic tolerance. As such, our study suggests that exposure of seedlings to T. inflatum GT22 VCs may be a means of improving crop productivity. This study describes a beneficial interaction between T. inflatun GT22 and Arabidopsis. Our investigation of microorganism function in terms of VC activities allowed us to overcome the limitations of traditional microbial application methods. The importance of this study lies in the discovery of T. inflatun GT22 as a beneficial microorganism. This soilborne fungus emits VCs with plant growth-promoting effects and the ability to alleviate both copper and pathogenic stress. Furthermore, our study offers a valuable approach to tracking the activities of fungal VC components via transcriptomic analysis and sheds light on the mechanisms through which VCs promote plant growth and induce resistance. This research significantly advances our knowledge of VC applications and provides an example for further investigations within this field.

Protein-protein interaction network-based integration of GWAS and functional data for blood pressure regulation analysis

BACKGROUND

It is valuable to analyze the genome-wide association studies (GWAS) data for a complex disease phenotype in the context of the protein-protein interaction (PPI) network, as the related pathophysiology results from the function of interacting polyprotein pathways. The analysis may include the design and curation of a phenotype-specific GWAS meta-database incorporating genotypic and eQTL data linking to PPI and other biological datasets, and the development of systematic workflows for PPI network-based data integration toward protein and pathway prioritization. Here, we pursued this analysis for blood pressure (BP) regulation.

METHODS

The relational scheme of the implemented in Microsoft SQL Server BP-GWAS meta-database enabled the combined storage of: GWAS data and attributes mined from GWAS Catalog and the literature, Ensembl-defined SNP-transcript associations, and GTEx eQTL data. The BP-protein interactome was reconstructed from the PICKLE PPI meta-database, extending the GWAS-deduced network with the shortest paths connecting all GWAS-proteins into one component. The shortest-path intermediates were considered as BP-related. For protein prioritization, we combined a new integrated GWAS-based scoring scheme with two network-based criteria: one considering the protein role in the reconstructed by shortest-path (RbSP) interactome and one novel promoting the common neighbors of GWAS-prioritized proteins. Prioritized proteins were ranked by the number of satisfied criteria.

RESULTS

The meta-database includes 6687 variants linked with 1167 BP-associated protein-coding genes. The GWAS-deduced PPI network includes 1065 proteins, with 672 forming a connected component. The RbSP interactome contains 1443 additional, network-deduced proteins and indicated that essentially all BP-GWAS proteins are at most second neighbors. The prioritized BP-protein set was derived from the union of the most BP-significant by any of the GWAS-based or the network-based criteria. It included 335 proteins, with ~ 2/3 deduced from the BP PPI network extension and 126 prioritized by at least two criteria. ESR1 was the only protein satisfying all three criteria, followed in the top-10 by INSR, PTN11, CDK6, CSK, NOS3, SH2B3, ATP2B1, FES and FINC, satisfying two. Pathway analysis of the RbSP interactome revealed numerous bioprocesses, which are indeed functionally supported as BP-associated, extending our understanding about BP regulation.

CONCLUSIONS

The implemented workflow could be used for other multifactorial diseases.

Serum/Plasma Proteome in Non-Malignant Liver Disease

The liver is the central metabolic organ and produces 85-90% of the proteins found in plasma. Accordingly, the plasma proteome is an attractive source of liver disease biomarkers that reflects the different cell types present in this organ, as well as the processes such as responses to acute and chronic injury or the formation of an extracellular matrix. In the first part, we summarize the biomarkers routinely used in clinical evaluations and their biological relevance in the different stages of non-malignant liver disease. Later, we describe the current proteomic approaches, including mass spectrometry and affinity-based techniques, that allow a more comprehensive assessment of the liver function but also require complex data processing. The many approaches of analysis and interpretation and their potential caveats are delineated. While these advances hold the promise to transform our understanding of liver diseases and support the development and validation of new liver-related drugs, an interdisciplinary collaboration is needed.

Epigenetic drug screening for trophoblast syncytialization reveals a novel role for MLL1 in regulating fetoplacental growth

BACKGROUND

Abnormal placental development is a significant factor contributing to perinatal morbidity and mortality, affecting approximately 5-7% of pregnant women. Trophoblast syncytialization plays a pivotal role in the establishment and maturation of the placenta, and its dysregulation is closely associated with several pregnancy-related disorders, including preeclampsia and intrauterine growth restriction. However, the underlying mechanisms and genetic determinants of syncytialization are largely unknown.

METHODS

We conducted a systematic drug screen using an epigenetic compound library to systematically investigate the epigenetic mechanism essential for syncytialization, and identified mixed lineage leukemia 1 (MLL1), a histone 3 lysine 4 methyltransferase, as a crucial regulator of trophoblast syncytialization. BeWo cells were utilized to investigate the role of MLL1 during trophoblast syncytialization. RNA sequencing and CUT&Tag were further performed to search for potential target genes and the molecular pathways involved. Human placenta tissue was used to investigate the role of MLL1 in TEA domain transcription factor 4 (TEAD4) expression and the upstream signaling during syncytialization. A mouse model was used to examine whether inhibition of MLL1-mediated H3K4me3 regulated placental TEAD4 expression and fetoplacental growth.

RESULTS

Genetic knockdown of MLL1 or pharmacological inhibition of the MLL1 methyltransferase complex (by MI-3454) markedly enhanced syncytialization, while overexpression of MLL1 inhibited forskolin (FSK)-induced syncytiotrophoblast formation. In human placental villous tissue, MLL1 was predominantly localized in the nuclei of cytotrophoblasts. Moreover, a notable upregulation in MLL1 expression was observed in the villus tissue of patients with preeclampsia compared with that in the control group. Based on RNA sequencing and CUT&Tag analyses, depletion of MLL1 inhibited the Hippo signaling pathway by suppressing TEAD4 expression by modulating H3K4me3 levels on the TEAD4 promoter region. TEAD4 overexpression significantly reversed the FSK-induced or MLL1 silencing-mediated trophoblast syncytialization. Additionally, decreased hypoxia-inducible factor 1A (HIF1A) enrichment at the MLL1 promoter was observed during syncytialization. Under hypoxic conditions, HIF1A could bind to and upregulate MLL1, leading to the activation of the MLL1/TEAD4 axis. In vivo studies demonstrated that the administration of MI-3454 significantly enhanced fetal vessel development and increased the thickness of the syncytial layer, thereby supporting fetoplacental growth.

CONCLUSIONS

These results revealed a novel epigenetic mechanism underlying the progression of syncytialization with MLL1, and suggest potential avenues for identifying new therapeutic targets for pregnancy-related disorders.

Longitudinal plasma proteome profiling reveals the diversity of biomarkers for diagnosis and cetuximab therapy response of colorectal cancer

Cetuximab therapy is the major treatment for colorectal cancer (CRC), but drug resistance limits its effectiveness. Here, we perform longitudinal and deep proteomic profiling of 641 plasma samples originated from 147 CRC patients (CRCs) undergoing cetuximab therapy with multi-course treatment, and 90 healthy controls (HCs). COL12A1, THBS2, S100A8, and S100A9 are screened as potential proteins to distinguish CRCs from HCs both in plasma and tissue validation cohorts. We identify the potential biomarkers (RRAS2, MMP8, FBLN1, RPTOR, and IMPDH2) for the initial response prediction. In a longitudinal setting, we identify two clusters with distinct fluctuations and construct the model with high accuracy to predict the longitudinal response, further validated in the independent cohort. This study reveals the heterogeneity of different biomarkers for tumor diagnosis, the initial and longitudinal response prediction respectively in the first course and multi-course cetuximab treatment, may ultimately be useful in monitoring and intervention strategies for CRC.

Upregulation of CCNB2 and a novel lncRNAs-related risk model predict prognosis in clear cell renal cell carcinoma

BACKGROUND

Clear cell renal cell carcinoma (ccRCC) is the main type of renal cell carcinoma. Cyclin B2 (CCNB2) is a subtype of B-type cyclin that is associated with the prognosis of several cancers. This study aimed to identify the relationship between CCNB2 and progression of ccRCC and construct a novel lncRNAs-related model to predict prognosis of ccRCC patients.

METHODS

The data were obtained from public databases. We identified CCNB2 in ccRCC using Kaplan-Meier survival analysis, univariate and multivariate Cox regression, and Gene Ontology analysis. External validation was then performed. The risk model was constructed based on prognostic lncRNAs by the LASSO algorithm and multivariate Cox regression. Receiver operating characteristics (ROC) curves were used to evaluate the model. Consensus clustering analysis was performed to re-stratify the patients. Finally, we analyzed the tumor-immune microenvironment and performed screening of potential drugs.

RESULTS

CCNB2 associated with late clinicopathological parameters and poor prognosis in ccRCC and was an independent predictor for disease-free survival. In addition, CCNB2 shared the same expression pattern with known suppressive immune checkpoints. A risk model dependent on the expression of three prognostic CCNB2-related lncRNAs (SNHG17, VPS9D1-AS1, and ZMIZ1-AS1) was constructed. The risk signature was an independent predictor of ccRCC. The area under the ROC (AUC) curve for overall survival at 1-, 3-, 5-, and 8-year was 0.704, 0.702, 0.741, and 0.763. The high-risk group and cluster 2 had stronger immunogenicity and were more sensitive to immunotherapy.

CONCLUSION

CCNB2 could be an important biomarker for predicting prognosis in ccRCC patients. Furthermore, we developed a novel lncRNAs-related risk model and identified two CCNB2-related molecular clusters. The risk model performed well in predicting overall survival and immunological microenvironment of ccRCC.

Analysis of SIGLEC12 expression, immunomodulation and prognostic value in renal cancer using multiomic databases

Siglecs belong to a family of immune regulatory receptors predominantly found on hematopoietic cells. They interact with Sia, resulting in the activation or inhibition of the immune response. Previous reports have suggested that the SIGLEC12 gene, which encodes the Siglec-XII protein, is expressed in the epithelial tissues and upregulated in carcinomas. However, studies deciphering the role of Siglec-XII in renal cancer (RC) are still unavailable, and here we provide insights on this question. We conducted expression analysis using the Human Protein Atlas and UALCAN databases. The impact of SIGLEC12 on RC prognosis was determined using the KM plotter, and an assessment of immune infiltration with SIGLEC12 was performed using the TIMER database. GSEA was conducted to identify the pathways affected by SIGLEC12. Finally, using GeneMania, we identified Siglec-XII interacting proteins. Our findings indicated that macrophages express SIGLEC12 in the kidney. Furthermore, we hypothesize that Siglec-XII expression might be involved in the increase of primary RC, but this effect may not be dependent on the age of the patient. In the tumour microenvironment, oncogenic pathways appeared to be upregulated by SIGLEC12. Similarly, our analysis suggested that SIGLEC12-related kidney renal papillary cell carcinomas may be more suitable for targeted immunotherapy, such as CTLA-4 and PD-1/PD-L1 inhibitors. These preliminary results suggested that high expression of SIGLEC12 is associated with poor prognosis for RC. Future studies to assess its clinical utility are necessitated.

Nanopore Direct RNA Sequencing Reveals the Short-Term Salt Stress Response in Maize Roots

Transcriptome analysis, relying on the cutting-edge sequencing of cDNA libraries, has become increasingly prevalent within functional genome studies. However, the dependence on cDNA in most RNA sequencing technologies restricts their ability to detect RNA base modifications. To address this limitation, the latest Oxford Nanopore Direct RNA Sequencing (ONT DRS) technology was employed to investigate the transcriptome of maize seedling roots under salt stress. This approach aimed to unveil both the RNA transcriptional profiles and alterations in base modifications. The analysis of the differential expression revealed a total of 1398 genes and 2223 transcripts that exhibited significant variation within the maize root system following brief exposure to salt stress. Enrichment analyses, such as the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway assessments, highlighted the predominant involvement of these differentially expressed genes (DEGs) in regulating ion homeostasis, nitrogen metabolism, amino acid metabolism, and the phytohormone signaling pathways. The protein-protein interaction (PPI) analysis showed the participation of various proteins related to glycolytic metabolism, nitrogen metabolism, amino acid metabolism, abscisic acid signaling, and the jasmonate signaling pathways. It was through this intricate molecular network that these proteins collaborated to safeguard root cells against salt-induced damage. Moreover, under salt stress conditions, the occurrence of variable shear events (AS) in RNA modifications diminished, the average length of poly(A) tails underwent a slight decrease, and the number of genes at the majority of the variable polyadenylation (APA) sites decreased. Additionally, the levels of N5-methylcytosine (m5C) and N6-methyladenosine (m6A) showed a reduction. These results provide insights into the mechanisms of early salt tolerance in maize.

Integrative analysis of LAG3 immune signature and identification of a LAG3-related genes prognostic signature in kidney renal clear cell carcinoma

Immune checkpoint blockade (ICB) therapy has resulted in improved overall survival in kidney renal clear cell carcinoma (KIRC), but most treated patients fail to show durable clinical responses. Lymphocyte activation gene-3 (LAG3) is a novel inhibitory immune checkpoint, but its expression pattern, prognostic value, and immunological role in KIRC remain unknown. In this study, we utilized TCGA_KIRC RNA-sequencing data to analyze the relationship between LAG3 expression and clinical features. The single-cell sequencing data and tissue immunofluorescence are employed to investigate the subcellular localization of LAG3 in KIRC. Kaplan-Meier plotter, TIMER, and TISIDB were used to assess the association between LAG3 expression and prognosis, as well as its correlation with immune-related components. We constructed the LAG3 interaction network by using STRING, GeneMANIA, BioGRID, and HitPredict databases. We found that LAG3 is upregulated and correlates with poor prognostic phenotype in KIRC. LAG3 is predominantly expressed on exhausted CD8+ T cells and shows strong co-expression with PDCD1 in KIRC. Moreover, our findings indicated that LAG3 not only inhibits T cell activation but also potentially regulates cell adhesion in KIRC. In conclusion, our study implies that LAG3 can serve as a potential prognostic biomarker for KIRC. Furthermore, blocking both LAG3 and PDCD1 may alleviate resistance to anti-PDCD1 therapy, providing novel insights for immunotherapy decision-making in KIRC patients.

Proteomic profiling of formalin-fixed paraffine-embedded tissue reveals key proteins related to lung dysfunction in idiopathic pulmonary fibrosis

Introduction

Idiopathic pulmonary fibrosis (IPF) severely affects the lung leading to aberrant deposition of extracellular matrix and parenchymal stiffness with progressive functional derangement. The limited availability of fresh tissues represents one of the major limitations to study the molecular profiling of IPF lung tissue. The primary aim of this study was to explore the proteomic profiling yield of archived formalin-fixed paraffin-embedded (FFPE) specimens of IPF lung tissues.

Methods

We further determined the protein expression according to respiratory functional decline at the time of biopsy. The total proteins isolated from 11 FFPE samples of IPF patients compared to 3 FFPE samples from a non-fibrotic lung defined as controls, were subjected to label-free quantitative proteomic analysis by liquid chromatography-mass spectrometry (LC-MS/MS) and resulted in the detection of about 400 proteins.

Results

After the pairwise comparison between controls and IPF, functional enrichment analysis identified differentially expressed proteins that were involved in extracellular matrix signaling pathways, focal adhesion and transforming growth factor β (TGF-β) signaling pathways strongly associated with IPF onset and progression. Five proteins were significantly over- expressed in the lung of IPF patients with either advanced disease stage (Stage II) or impaired pulmonary function (FVC<75, DLCO<55) compared to controls; these were lymphocyte cytosolic protein 1 (LCP1), peroxiredoxin-2 (PRDX2), transgelin 2 (TAGLN2), lumican (LUM) and mimecan (OGN) that might play a key role in the fibrogenic processes.

Discussion

Our work showed that the analysis of FFPE samples was able to identify key proteins that might be crucial for the IPF pathogenesis. These proteins are correlated with lung carcinogenesis or involved in the immune landscape of lung cancer, thus making possible common mechanisms between lung carcinogenesis and fibrosis progression, two pathological conditions at risk for each other in the real life.

TDP-43-stratified single-cell proteomics of postmortem human spinal motor neurons reveals protein dynamics in amyotrophic lateral sclerosis

A limitation of conventional bulk-tissue proteome studies in amyotrophic lateral sclerosis (ALS) is the confounding of motor neuron (MN) signals by admixed non-MN proteins. Here, we leverage laser capture microdissection and nanoPOTS single-cell mass spectrometry-based proteomics to query changes in protein expression in single MNs from postmortem ALS and control tissues. In a follow-up analysis, we examine the impact of stratification of MNs based on cytoplasmic transactive response DNA-binding protein 43 (TDP-43)+ inclusion pathology on the profiles of 2,238 proteins. We report extensive overlap in differentially abundant proteins identified in ALS MNs with or without overt TDP-43 pathology, suggesting early and sustained dysregulation of cellular respiration, mRNA splicing, translation, and vesicular transport in ALS. Together, these data provide insights into proteome-level changes associated with TDP-43 proteinopathy and begin to demonstrate the utility of pathology-stratified trace sample proteomics for understanding single-cell protein dynamics in human neurologic diseases.

Differences in aqueous humor protein profiles in patients with proliferative diabetic retinopathy before and after aflibercept treatment

PURPOSE

To investigate the changes in aqueous humor (AH) protein profiles before and after intravitreal aflibercept (IVA) treatment in patients with proliferative diabetic retinopathy (PDR).

METHODS

5 PDR patients provided 10 samples of AH before and after IVA treatment (pre-group vs. post-group). Proteins were identified using liquid chromatography-tandem mass spectrometry. Then, bioinformatics was employed to investigate the functional significance of differentially expressed proteins (DEPs) and hub proteins.

RESULTS

A total of 16 DEPs were identified, consisting of 8 downregulated proteins and 8 upregulated proteins. Bioinformatics analysis indicated that the most significantly enriched biological process was "blood coagulation, intrinsic pathway." The most significantly enriched signaling pathway was "complement and coagulation cascades." HBB, HPX, VEGFA, and CA1 were identified as hub proteins for IVA treatment.

CONCLUSIONS

Together with the downregulation of the intravitreal vascular endothelial growth factor level, IVA may also change the AH protein composition in PDR patients, with DEPs involved in the blood coagulation, intrinsic pathway, complement, and coagulation cascades. IVA treatment may protect against PDR by regulating HBB, HPX, VEGFA, and CA1 expression.

Multiplexed MRM-based proteomics for identification of circulating proteins as biomarkers of cardiovascular damage progression associated with diabetes mellitus

BACKGROUND

Type 2 diabetes mellitus (T2DM) increases the risk of coronary heart disease (CHD) by 2-4 fold, and is associated with endothelial dysfunction, dyslipidaemia, insulin resistance, and chronic hyperglycaemia. The aim of this investigation was to assess, by a multimarker mass spectrometry approach, the predictive role of circulating proteins as biomarkers of cardiovascular damage progression associated with diabetes mellitus.

METHODS

The study considered 34 patients with both T2DM and CHD, 31 patients with T2DM and without CHD, and 30 patients without diabetes with a diagnosis of CHD. Plasma samples of subjects were analysed through a multiplexed targeted liquid chromatography mass spectrometry (LC-MS)-based assay, namely Multiple Reaction Monitoring (MRM), allowing the simultaneous detection of peptides derived from a protein of interest. Gene Ontology (GO) Analysis was employed to identify enriched GO terms in the biological process, molecular function, or cellular component categories. Non-parametric multivariate methods were used to classify samples from patients and evaluate the relevance of the analysed proteins' panel.

RESULTS

A total of 81 proteins were successfully quantified in the human plasma samples. Gene Ontology analysis assessed terms related to blood microparticles, extracellular exosomes and collagen-containing extracellular matrix. Preliminary evaluation using analysis of variance (ANOVA) of the differences in the proteomic profile among patient groups identified 13 out of the 81 proteins as significantly different. Multivariate analysis, including cluster analysis and principal component analysis, identified relevant grouping of the 13 proteins. The first main cluster comprises apolipoprotein C-III, apolipoprotein C-II, apolipoprotein A-IV, retinol-binding protein 4, lysozyme C and cystatin-C; the second one includes, albeit with sub-grouping, alpha 2 macroglobulin, afamin, kininogen 1, vitronectin, vitamin K-dependent protein S, complement factor B and mannan-binding lectin serine protease 2. Receiver operating characteristic (ROC) curves obtained with the 13 selected proteins using a nominal logistic regression indicated a significant overall distinction (p < 0.001) among the three groups of subjects, with area under the ROC curve (AUC) ranging 0.91-0.97, and sensitivity and specificity ranging from 85 to 100%.

CONCLUSIONS

Targeted mass spectrometry approach indicated 13 multiple circulating proteins as possible biomarkers of cardiovascular damage progression associated with T2DM, with excellent classification results in terms of sensitivity and specificity.

Cronobacter sakazakii infection implicates multifaceted neuro-immune regulatory pathways of Caenorhabditis elegans

The neural pathways of Caenorhabditis elegans play a crucial role in regulating host immunity and inflammation during pathogenic infections. To understand the major neuro-immune signaling pathways, this study aimed to identify the key regulatory proteins in the host C. elegans during C. sakazakii infection. We used high-throughput label-free quantitative proteomics and identified 69 differentially expressed proteins. KEGG analysis revealed that C. sakazakii elicited host immune signaling cascades primarily including mTOR signaling, axon regeneration, metabolic pathways (let-363 and acox-1.4), calcium signaling (mlck-1), and longevity regulating pathways (ddl-2), respectively. The abrogation in functional loss of mTOR-associated players deciphered that C. sakazakii infection negatively regulated the lifespan of mutant worms (akt-1, let-363 and dlk-1), including physiological aberrations, such as reduced pharyngeal pumping and egg production. Additionally, the candidate pathway proteins were validated by transcriptional profiling of their corresponding genes. Furthermore, immunoblotting showed the downregulation of mTORC2/SGK-1 during the later hours of pathogen exposure. Overall, our findings profoundly provide an understanding of the specificity of proteome imbalance in affecting neuro-immune regulations during C. sakazakii infection.

Socioeconomic inequalities in early adulthood disrupt the immune transcriptomic landscape via upstream regulators

Disparities in socio-economic status (SES) predict many immune system-related diseases, and previous research documents relationships between SES and the immune cell transcriptome. Drawing on a bioinformatically-informed network approach, we situate these findings in a broader molecular framework by examining the upstream regulators of SES-associated transcriptional alterations. Data come from the National Longitudinal Study of Adolescent to Adult Health (Add Health), a nationally representative sample of 4543 adults in the United States. Results reveal a network-of differentially expressed genes, transcription factors, and protein neighbors of transcription factors-that shows widespread SES-related dysregulation of the immune system. Mediational models suggest that body mass index (BMI) plays a key role in accounting for many of these associations. Overall, the results reveal the central role of upstream regulators in socioeconomic differences in the molecular basis of immunity, which propagate to increase risk of chronic health conditions in later-life.

Using multi-scale genomics to associate poorly annotated genes with rare diseases

BACKGROUND

Next-generation sequencing (NGS) has significantly transformed the landscape of identifying disease-causing genes associated with genetic disorders. However, a substantial portion of sequenced patients remains undiagnosed. This may be attributed not only to the challenges posed by harder-to-detect variants, such as non-coding and structural variations but also to the existence of variants in genes not previously associated with the patient's clinical phenotype. This study introduces EvORanker, an algorithm that integrates unbiased data from 1,028 eukaryotic genomes to link mutated genes to clinical phenotypes.

METHODS

EvORanker utilizes clinical data, multi-scale phylogenetic profiling, and other omics data to prioritize disease-associated genes. It was evaluated on solved exomes and simulated genomes, compared with existing methods, and applied to 6260 knockout genes with mouse phenotypes lacking human associations. Additionally, EvORanker was made accessible as a user-friendly web tool.

RESULTS

In the analyzed exomic cohort, EvORanker accurately identified the "true" disease gene as the top candidate in 69% of cases and within the top 5 candidates in 95% of cases, consistent with results from the simulated dataset. Notably, EvORanker outperformed existing methods, particularly for poorly annotated genes. In the case of the 6260 knockout genes with mouse phenotypes, EvORanker linked 41% of these genes to observed human disease phenotypes. Furthermore, in two unsolved cases, EvORanker successfully identified DLGAP2 and LPCAT3 as disease candidates for previously uncharacterized genetic syndromes.

CONCLUSIONS

We highlight clade-based phylogenetic profiling as a powerful systematic approach for prioritizing potential disease genes. Our study showcases the efficacy of EvORanker in associating poorly annotated genes to disease phenotypes observed in patients. The EvORanker server is freely available at https://ccanavati.shinyapps.io/EvORanker/ .

An Enzymatic Cofactor Regeneration System for the in-Vitro Reduction of Isolated C=C Bonds by Geranylgeranyl Reductases

Cofactor regeneration systems are of major importance for the applicability of oxidoreductases in biocatalysis. Previously, geranylgeranyl reductases have been investigated for the enzymatic reduction of isolated C=C bonds. However, an enzymatic cofactor-regeneration system for in vitro use is lacking. In this work, we report a ferredoxin from the archaea Archaeoglobus fulgidus that regenerates the flavin of the corresponding geranylgeranyl reductase. The proteins were heterologously produced, and the regeneration was coupled to a ferredoxin reductase from Escherichia coli and a glucose dehydrogenase from Bacillus subtilis, thereby enabling the reduction of isolated C=C bonds by purified enzymes. The system was applied in crude, cell-free extracts and gave conversions comparable to those of a previous method using sodium dithionite for cofactor regeneration. Hence, an enzymatic approach to the reduction of isolated C=C bonds can be coupled with common systems for the regeneration of nicotinamide cofactors, thereby opening new perspectives for the application of geranylgeranyl reductases in biocatalysis.

Exploring shared therapeutic targets in diabetic cardiomyopathy and diabetic foot ulcers through bioinformatics analysis

Advanced diabetic cardiomyopathy (DCM) patients are often accompanied by severe peripheral artery disease. For patients with DCM combined with diabetic foot ulcer (DFU), there are currently no good therapeutic targets and drugs. Here, we investigated the underlying network of molecular actions associated with the occurrence of these two complications. The datasets were downloaded from the Gene Expression Omnibus (GEO) database. We performed enrichment and protein-protein interaction analyses, and screened for hub genes. Construct transcription factors (TFs) and microRNAs regulatory networks for validated hub genes. Finally, drug prediction and molecular docking verification were performed. We identified 299 common differentially expressed genes (DEGs), many of which were involved in inflammation and lipid metabolism. 6 DEGs were identified as hub genes (PPARG, JUN, SLC2A1, CD4, SCARB1 and SERPINE1). These 6 hub genes were associated with inflammation and immune response. We identified 31 common TFs and 2 key miRNAs closely related to hub genes. Interestingly, our study suggested that fenofibrate, a lipid-lowering medication, holds promise as a potential treatment for DCM combined with DFU due to its stable binding to the identified hub genes. Here, we revealed a network involves a common target for DCM and DFU. Understanding these networks and hub genes is pivotal for advancing our comprehension of the multifaceted complications of diabetes and facilitating the development of future therapeutic interventions.

Quantitative proteomics based on TMT revealed the response of PK15 cells infected PEDV wild strain

Porcine epidemic diarrhea (PED), caused by porcine epidemic diarrhea virus (PEDV), is an acute and highly contagious enteric disease with a high mortality rate in suckling piglets. Identification of proteins associated with PEDV infection may provide insights into the pathogenesis of this viral disease. In this study, we employed tandem mass tag (TMT) quantitative protein analysis to investigate proteomic changes in PK15 cells following PEDV infection, and differential protein expression profiles were obtained at 0 h, 24 h, and 48 h post-infection. Overall, a total of 6330 proteins were identified. Applying criteria for fold change >1.5 < 0.67 and p-values <0.05 resulted in the identification of 59 up-regulated proteins and 103 down-regulated proteins that exhibited significant alterations in the H24 group compared to the H0 group. The H48 group demonstrated significant upregulation of 110 proteins and downregulation of 144 proteins compared to the H0 group; additionally, there were also 10 upregulated and 30 downregulated proteins in the H48 group when compared to the H24 group. These differentially expressed proteins (DEPs) were involved in immune response regulation, signal transduction, lipid transport and metabolism processes as well as cell apoptosis pathways. Based on these DEPs, we propose that PEDV may disrupt signal transduction pathways along with lipid transport and metabolism processes leading to maximal viral replication, it may also trigger inflammatory cascades accordingly. These findings could provide valuable information for elucidating specific pathogenesis related to PEDV infection while contributing towards developing new antiviral strategies.

Identification of hub genes and pathways associated with cellular senescence in diabetic foot ulcers via comprehensive transcriptome analysis

This research aimed to find important genes and pathways related to cellular senescence (CS) in diabetic foot ulcers (DFU) and to estimate the possible pathways through which CS affects diabetic foot healing. The GSE80178 dataset was acquired from the Gene Expression Omnibus (GEO) database, containing six DFU and three diabetic foot skin (DFS) samples. The limma package was used to identify differentially expressed genes (DEGs). At the same time, DEGs associated with CS (CS-DEGs) were found using the CellAge database. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were conducted on the CS-DEGs. A protein-protein interaction (PPI) network was built using the String database, and the cytoHubba plug-in within Cytoscape helped identify hub genes. Lastly, the miRNA-TF-mRNA regulatory network for these hub genes was established. In total, 66 CS-DEGs were obtained. These genes mainly focus on CS, Kaposi sarcoma-associated herpesvirus infection and Toll-like receptor signalling pathway. Eight hub genes were identified to regulate cell senescence in DFU, including TP53, SRC, SIRT1, CCND1, EZH2, CXCL8, AR and CDK4. According to miRNA-TF-mRNA regulatory network, hsa-mir-132-3p/SIRT1/EZH2 axis is involved in senescence cell accumulation in DFU.

ZC3H12A inhibits tumor growth and metastasis of breast cancer under hypoxic condition via the inactivation of IL-17 signaling pathway

Hypoxia is a major contributor to tumor microenvironment (TME) and metastasis in most solid tumors. We seek to screen hypoxia-related genes affecting metastasis in breast cancer and to reveal relative potential regulatory pathway. Based on gene expression profiling of GSE17188 dataset, differential expressed genes (DEGs) were identified between highly metastatic breast cancer cells under hypoxia and samples under normoxia. The protein-protein interaction (PPI) network was utilized to determine hub genes. The gene expression profiling interactive analysis database (GEPIA2) and quantitative reverse-transcription polymerase chain reaction (qRT-PCR) were employed to quantify hub genes. Moreover, overexpression of zinc finger CCCH-type containing 12A (ZC3H12A) was performed both in breast cancer cells and xenograft mouse model to determine the role of ZC3H12A. We identified 134 DEGs between hypoxic and normoxic samples. Based on PPI analysis, 5 hub genes interleukin (IL)-6, GALN (GAL), CD22 molecule (CD22), ZC3H12A and TNF receptor associated factor 1 (TRAF1) were determined; the expression levels of TRAF1, IL-6, ZC3H12A and GAL were remarkably downregulated while CD22 was upregulated in breast cancer cells. Besides, patients with higher expression of ZC3H12A had favorable prognosis. Overexpression of ZC3H12A could inhibit metastasis and tumor growth of breast cancer; overexpression of ZC3H12A downregulated the expression of IL-17 signaling pathway-related proteins such as IL-17 receptor A (IL-17RA), IL-17A and nuclear factor κB activator 1 (Act1). This study reveals ZC3H12A and IL-17 signaling pathway as potential therapeutic targets for hypoxic breast cancer.